Interpretational challenges of the Win Ratio in analyzing Hierarchical Composite Endpoints in Chronic Kidney Disease
慢性肾病分层复合终点分析中胜率比的解释难题AI 解读 ↓
本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。
本页为预印本版本;arXiv 收录、作者填写的期刊信息以及作者既有发表经历,都不单独证明本篇已接收。作者发表记录按 OpenAlex 身份与完整姓名、本站覆盖期刊 ISSN 及正式卷期核对,只展示已核实例,档案仍可能误合并。
引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。
AI 根据所提供的论文材料归类:摘要明确讨论治疗效应目标量及其背后的因果问题,直接涉及因果推断的解释。
慢性肾病分层复合终点分析中胜率比的解释难题AI 解读 ↓
正在核对关联版本…
正在核对对应版本的资源…
Win statistics based methods have gained traction as a method for analyzing Hierarchical Composite Endpoints (HCEs) in randomized clinical trials, particularly in cardiovascular and kidney disease research. HCEs offer several key advantages, including increased statistical power, mitigation of competing risks, and hierarchical ranking of clinical outcomes. While, as summary measures, the win ratio (WR) along with the Net Benefit (NB) and the Win Odds (WO) provide a structured approach to analyzing HCEs, several concerns regarding their interpretability remain. In this paper, we present known issues with the WR using simple examples designed to explore the implications for the clinical interpretability of the treatment effect measure in the chronic kidney disease setting. Specifically, we discuss the challenge of defining an appropriate estimand in the context of HCEs using the WR, the difficulties in formulating a relevant causal question underlying the WR, and the dependency of the WR on the variance of its components, which complicates its role as an effect measure. Additionally, we highlight the non-collapsibility and non-transitivity of the WR, further complicating its interpretation. While the WR remains a valuable tool in clinical trials, its inherent limitations must be acknowledged to ensure its proper use in regulatory and clinical decision-making.